Optical character recognition has used various methods in the past. Methods used include various forms of feature extraction, flying spot scanners, and correlation techniques. The flying spot scanner approach is limited in that a special non-imaging sensor is utilized and requires the position of the characters to be fairly well controlled. Feature extraction techniques have difficulty with noisy video signals. Correlation approaches work better than other methods of character recognition for noisy signals, but are generally too slow for practical use unless the position of the characters is well known.
In earlier system designs, some required quantizing the input video into two binary levels. In these earlier systems only the edge information was retained. For such schemes the video signal was differentiated, and usually rectified, to produce voltage spikes when the input video level changed. The amplitude of these voltage spikes is a function of how rapidly the video input changes level. Therefore, DC and low frequency information is lost. This quantizing technique causes the noise on the video input to be accentuated and allows the information that exists between the edges of the characters to be lost. The feature extraction concept relies on this information to locate valid characters.
Another technique often used to quantize an analog signal into a two level binary signal involves establishing a threshold level and letting signals above this threshold be "1" and signals below the threshold be a "0". This method works quite well, providing the proper threshold level has been set. If the threshold level is set above or below the portion of the signal to be quantized, the output will remain constant and the information will be lost.